Expert System for Automatically Correcting OCR Output
Meeting name
Document Recognition
Document Type
Conference Proceeding
Meeting location
San Jose, CA
Publication Date
2-6-1994
Abstract
This paper describes a new expert system for automatically correcting errors made by optical character recognition (OCR) devices. The system, which we call the post-processing system, is designed to improve the quality of text produced by an OCR device in preparation for subsequent retrieval from an information system. The system is composed of numerous parts: an information retrieval system, an English dictionary, a domain-specific dictionary, and a collection of algorithms and heuristics designed to correct as many OCR errors as possible. For the remaining errors that cannot be corrected, the system passes them on to a user-level editing program. This post-processing system can be viewed as part of a larger system that would streamline the steps of taking a document from its hard copy form to its usable electronic form, or it can be considered a stand alone system for OCR error correction. An earlier version of this system has been used to process approximately 10,000 pages of OCR generated text. Among the OCR errors discovered by this version, about 87% were corrected. We implement numerous new parts of the system, test this new version, and present the results.
Keywords
Electronic data processing; Errors; Optical character recognition; Optical character recognition devices; Optical pattern recognition
Disciplines
Computer Engineering | Computer Sciences | Electrical and Computer Engineering | Software Engineering | Theory and Algorithms
Permissions
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Repository Citation
Taghva, K.,
Borsack, J.,
Condit, A.
(1994, February).
Expert System for Automatically Correcting OCR Output.
Presentation at Document Recognition,
San Jose, CA.
Available at: https://digitalscholarship.unlv.edu/ece_presentations/37